The increasing global emphasis on sustainable transportation drives the need for strong electric vehicle (EV) charging networks. While national plans set high targets for EV adoption, translating these into practical infrastructure placement poses a significant hurdle. This study tackles this by creating detailed maps to show suitable locations for EV charging stations (EVCS) across the Attica region of Greece. Our main approach combines Geographic Information System (GIS) with Multi-Criteria Decision-Making (MCDM), specifically using the Analytic Hierarchy Process (AHP). After reviewing existing research to find important location factors, we adjusted these to fit the unique urban and social features of metropolitan Athens. We established four main criteria, accessibility, social, energy, and environmental, which were then divided into nine sub-criteria for our analysis. We developed four different models, each applying a unique weighting to these criteria (basic, energy-focused, environmental, and social) to see how various planning goals affect spatial outcomes. These models generated graded suitability maps, highlighting areas with high potential for new infrastructure. Central Athens consistently showed the highest suitability, which matches current research and confirms our method’s reliability. This work provides a useful, repeatable framework for local governments to strategically deploy EVCS, supporting urban planning and helping meet national goals for decarbonization and air quality.

The transportation sector is responsible for over 20% of Europe’s CO₂ emissions, significantly worsening urban air quality and compromising public health. Electric vehicles (EVs)—namely BEVs and PHEVs—offer some relief by lowering noise and pollution in urban settings. Nevertheless, their effectiveness in benefiting the environment relies on the current electricity generation mix. In accordance with national energy goals, this study evaluates the environmental effects of EV adoption in Greece until 2035, utilizing a scenario-based approach grounded in the forecasts of the Greek National Energy and Climate Plan. Three different electrification pathways are examined to explore how varying levels of electric vehicle adoption and progress in decarbonizing the power sector could reduce air pollution, particularly in cities. By comparing the projected CO₂, CO, NO_x, PM₁₀, and SO₂ pollutant output from BEVs and PHEVs with those of internal combustion engine vehicles, the study highlights the significance of integrating renewable energy sources and assesses the potential for EVs to reduce emissions within Greece’s changing energy mix.

Increased interest is demonstrated recently in the emergence of prosumer schemes for the residential sector on the basis of combined RES and storage configurations. Primarily, such schemes aim to increase energy autonomy for end users. Despite providing an alternative supply solution that may secure end users from volatile energy prices, RES–battery configurations also suggest costly and, in most cases, capital-intensive solutions. As such, exploring the generation of additional revenue through market participation is an exercise worth undertaking, noting at the same time that decongestion management services may also be provided to the local grid. In this context, the current study introduces an operational framework for the market participation of RES–battery prosumer schemes, seeking to determine the optimal balance between self-consumption and market integration. For that purpose, we use typical demand patterns and perform an extensive parametrical analysis concerning system size, spot price levels and degree of market integration in the context of the Greek electricity market, with our results indicating areas of optimum balance for the minimization of similar schemes’ levelized cost of electricity.

This work focuses on examining the contribution of passenger cars to CO₂, NO_X, CO, PM₁₀, and NMVOC emissions, as well as the changes in future emissions resulting from the usage of different types of vehicles. Initially, the importance of the road transport sector is discussed, followed by a presentation of data regarding the vehicle fleet. Subsequently, a methodology for forecasting the fleet, and calculating emissions, is introduced. Finally, the results are presented, focusing on the release of gaseous pollutants under different possible scenarios regarding the extent of electric vehicle penetration into the passenger vehicle fleet, for the year 2030.

The specific research presents a detailed, data-driven energy analysis on the early-life operation of two rooftop photovoltaic (PV) systems. The two PV systems examined are operated under the Net Metering scheme and are found in close proximity, within the geographical boundaries of a small-scale remote island on the Southeastern part of the Aegean Sea, Greece. The systems feature similar PV technology and capacity, i.e., 3.5 kW_p vs. 5 kW_p, but differ in terms of installation characteristics; thus, they offer an interesting case for pairwise comparison. Supported by the exploitation of a wealthy set of data, a detailed energy analysis is conducted, with our results providing useful insights on the seasonal performance variation of the two systems and its determinants, reflecting on the different siting and installation characteristics of the former.

Occurrence of wind energy curtailments in non-interconnected island systems of considerable wind power capacity comes as a result of local grid limitations and significant load variation across seasons. Facilitating increased wind energy generation requires flexibility means such as energy storage and/or demand response (DR), with the latter presenting the advantage of suggesting a non-capital-intensive solution. To that end, in the present study we examine the problem of assessing day-ahead demand response requirements for the recovery of wind energy curtailments and put forward a stochastic approach, supported by the employment of artificial neural networks’ forecasting models and the integration of prediction uncertainties. For the application of our methodology, we use data from the non-interconnected island system of Kos and Kalymnos in the SE Aegean Sea and investigate the dynamics of the proposed DR scheme on the island of Tilos, belonging to the electricity complex of Kos and Kalymnos. At the same time, we perform a parametrical analysis so as to study the impact of appreciating different levels of available DR capacity, with our findings comparing favorably against the results of applying a deterministic approach.